
% THIS IS SIGPROC-SP.TEX - VERSION 3.1
% WORKS WITH V3.2SP OF ACM_PROC_ARTICLE-SP.CLS
% APRIL 2009
%
% It is an example file showing how to use the 'acm_proc_article-sp.cls' V3.2SP
% LaTeX2e document class file for Conference Proceedings submissions.
% ----------------------------------------------------------------------------------------------------------------
% This .tex file (and associated .cls V3.2SP) *DOES NOT* produce:
%       1) The Permission Statement
%       2) The Conference (location) Info information
%       3) The Copyright Line with ACM data
%       4) Page numbering
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% It is an example which *does* use the .bib file (from which the .bbl file
% is produced).
% REMEMBER HOWEVER: After having produced the .bbl file,
% and prior to final submission,
% you need to 'insert'  your .bbl file into your source .tex file so as to provide
% ONE 'self-contained' source file.
%
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% Questions/suggestions regarding the guidelines, .tex and .cls files, etc. to
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% For tracking purposes - this is V3.1SP - APRIL 2009

\documentclass{acm_proc_article-sp}

\begin{document}

\title{SERIMI: Class-based Disambiguation for Effective Instance Matching over Heterogeneous Web Data}

%\begin{document}

%\title{SERIMI: Class-based Disambiguation for Effective Instance Matching over Heterogeneous Web Data}
 
%
% You need the command \numberofauthors to handle the 'placement
% and alignment' of the authors beneath the title.
%
% For aesthetic reasons, we recommend 'three authors at a time'
% i.e. three 'name/affiliation blocks' be placed beneath the title.
%
% NOTE: You are NOT restricted in how many 'rows' of
% "name/affiliations" may appear. We just ask that you restrict
% the number of 'columns' to three.
%
% Because of the available 'opening page real-estate'
% we ask you to refrain from putting more than six authors
% (two rows with three columns) beneath the article title.
% More than six makes the first-page appear very cluttered indeed.
%
% Use the \alignauthor commands to handle the names
% and affiliations for an 'aesthetic maximum' of six authors.
% Add names, affiliations, addresses for
% the seventh etc. author(s) as the argument for the
% \additionalauthors command.
% These 'additional authors' will be output/set for you
% without further effort on your part as the last section in
% the body of your article BEFORE References or any Appendices.

\numberofauthors{5} %  in this sample file, there are a *total*
% of EIGHT authors. SIX appear on the 'first-page' (for formatting
% reasons) and the remaining two appear in the \additionalauthors section.
%
\author{
% You can go ahead and credit any number of authors here,
% e.g. one 'row of three' or two rows (consisting of one row of three
% and a second row of one, two or three).
%
% The command \alignauthor (no curly braces needed) should
% precede each author name, affiliation/snail-mail address and
% e-mail address. Additionally, tag each line of
% affiliation/address with \affaddr, and tag the
% e-mail address with \email.
% 
% 1st. author
\alignauthor 
Samur Araujo \\
     \affaddr{Delft University of Technology}\\     
       \affaddr{Delft, the Netherlands}\\
       \email{s.f.cardosodearaujo@tudelft.nl}
% 2nd. author
\alignauthor Duc Thanh Tran \\
       \affaddr{Karlsruher Institute of Technology}\\ 
       \affaddr{ Germany}\\
       \email{ducthanh.tran@kit.edu}       
% 3rd. author
\alignauthor 
Arjen P. de Vries \\
     \affaddr{Delft University of Technology}\\     
       \affaddr{Delft, the Netherlands}\\
       \email{a.p.devries@itudelft.nl}\\
       \and 
% 4th. author
\alignauthor 
Jan Hidders \\
     \affaddr{Delft University of Technology}\\     
       \affaddr{Delft, the Netherlands}\\
       \email{a.j.h.hidders@tudelft.nl}
 % use '\and' if you need 'another row' of author names
% 5th. author
\alignauthor 
Daniel Schwabe \\
       \affaddr{Informatics Department PUC-Rio}\\     
       \affaddr{ Rio de Janeiro, Brazil}\\
       \email{dschwabe@inf.puc-rio.br}
}
\maketitle
\begin{abstract} 
 
Instance matching has been studied with focus on the single-domain setting, 
%where data come from the same or similar datasets, 
while less attention is given to the 
%large and 
heterogeneous environment of the Web, where data comes from different domains and are associated with different schemas.  For this heterogeneous setting, we propose an unsupervised schema-agnostic approach that focuses on the refinement (\emph{disambiguation}) of candidate instances (resulting from blocking).  Given instances of a source dataset that belong to a class,  
it computes candidates in the target datasets and refines them such that the \emph{remaining matches correspond to the source instances at the class level}. However, no schema knowledge and explicit correspondences between classes in the source and target datasets are required for this. Rather, the disambiguation is performed based on an \emph{instance-based representation of classes} computed online. We evaluated our work using experiments on large-scale real-world datasets provided by a benchmark. 
%, showing promising results. 
The proposed solution outperformed two alternative approaches for instance matching in 70\% of the cases, and in those cases we improved average F-measure by 10\%. 

\end{abstract} 

\category{H.2.4}{Database Management}{Systems}
\category{H.2.5}{Database Management}{Heterogeneous Databases}
 
\keywords{data integration, instance matching, linked data} % NOT required for Proceedings
  
\input{sec-intro}
\input{sec-related}
\input{sec-problem}
\input{sec-approach}
\input{sec-experiment}

\section{Conclusions}
We investigated the instance matching problem in the large and heterogeneous environment of the Web. We proposed SERIMI as a completely unsupervised schema-agnostic approach that focuses on the effective matching of candidate instances (resulting from blocking). Our approach was able to refine the ambiguous matches provided by existing blocking techniques. 
%We evaluated the accuracy of SERIMI based on experiments on large-scale real-world datasets. 
We outperformed two alternative approaches approaches in 70\% of the cases, and in those cases we improved F1 by 10\% on average. Our approach is especially recommended in situations where there are few overlaps between the source and target schemas (i.e. where traditional single domain approaches are not applicable). 

\bibliographystyle{abbrv}
\bibliography{eswc}
\end{document}
